We don’t talk about Quarto

Quarto excitement!

Quarto excitement, in Python!

Others had more Quarto questions…

So what is Quarto?

So what is Quarto?

Quarto® is an open-source scientific and technical publishing system built on Pandoc.

thomasmock$ quarto --help

  Usage:   quarto
  Version: 1.0.36

  Options:
    -h, --help     - Show this help.                            
    -V, --version  - Show the version number for this program.  

  Commands:
    render          [input] [args...]   - Render input file(s) to various document types.            
    preview         [file] [args...]    - Render and preview a document or website project.          
    serve           [input]             - Serve a Shiny interactive document.                        
    create-project  [dir]               - Create a project for rendering multiple documents          
    convert         <input>             - Convert documents to alternate representations.            
    pandoc          [args...]           - Run the version of Pandoc embedded within Quarto.          
    run             [script] [args...]  - Run a TypeScript, R, Python, or Lua script.                
    install         <type> [target]     - Installs an extension or global dependency.                
    publish         [provider] [path]   - Publish a document or project. Available providers include:
    check           [target]            - Verify correct functioning of Quarto installation.         

RMarkdown for literate programming

Quarto for literate programming

Quarto for literate programming

So what is a .qmd?

A Quarto document i.e. a .qmd is a plain text file

format: html
engine: knitr

format: html
engine: jupyter

```{r}
library(dplyr)

mtcars |> 
  dplyr::group_by(cyl) |> 
  dplyr::summarize(mean = mean(mpg))
```

```{python}
from siuba import _, group_by, summarize
from siuba.data import mtcars
(mtcars
  >> group_by(_.cyl)
  >> summarize(avg_mpg = _.mpg.mean())
  )
```

# Heading 1
This is a sentence with some **bold text**, some *italic text* and an 
![image](image.png){fig-alt="Alt text for this image"}.

Patrick

One install, “Batteries included”

• Quarto’s 1.0 release comes pre-installed with RStudio v2022.07.1 and beyond! Any language, same syntax and approach

Many Quarto formats

roam in color

Comfort of your own workspace

Auto-completion in RStudio + VSCode

Both RStudio and VSCode with the Quarto extension have rich auto-completion

Interactivity with {htmlwidgets} or shiny

library(leaflet)
leaflet() %>%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lng=-77.0147, lat=38.7818, popup="We are here, together!")

Interactivity with Jupyter Widgets

from ipyleaflet import Map, Marker, basemaps, basemap_to_tiles
m = Map(
  basemap=basemap_to_tiles(
    basemaps.NASAGIBS.ModisTerraTrueColorCR, "2017-04-08"
  ),
  center=(38.7818, -77.0147),
  zoom=4
)
m.add_layer(Marker(location=(38.7818, -77.0147)))
m

Interactivity

Quarto also includes native support for Observable JS, a set of enhancements to vanilla JavaScript created by Mike Bostock (also the author of D3)

viewof bill_length_min = Inputs.range(
  [32, 50], 
  {value: 35, step: 1, label: "Bill length (min):"}
)
viewof islands = Inputs.checkbox(
  ["Torgersen", "Biscoe", "Dream"], 
  { value: ["Torgersen", "Biscoe"], 
    label: "Islands:"
  }
)

Plot.rectY(filtered, 
  Plot.binX(
    {y: "count"}, 
    {x: "body_mass", fill: "species", thresholds: 20}
  ))
  .plot({
    facet: {
      data: filtered,
      x: "sex",
      y: "species",
      marginRight: 80
    },
    marks: [
      Plot.frame(),
    ]
  }
)

Inputs.table(filtered)

data = FileAttachment("palmer-penguins.csv").csv({ typed: true })

filtered = data.filter(function(penguin) {
  return bill_length_min < penguin.bill_length &&
         islands.includes(penguin.island);
})

Next-Gen RMarkdown, unification

RMarkdown is not going away, but new features built into knitr and Quarto

quarto render my-favorite.rmd --to html

Next-Gen RMarkdown, extended for other languages

The main technical difference between Quarto and R Markdown is that Quarto makes heavy use of Pandoc’s Lua filters. - Yihui Xie ¹

What to do with my existing .ipynb?

quarto render my-favorite.ipynb --to html --execute

quarto convert --help

Usage:   quarto convert <input>

Description:

    Convert documents to alternate representations.

Convert notebook to markdown:                quarto convert doc.ipynb                
Convert markdown to notebook:                quarto convert doc.qmd                  
Convert notebook to markdown, write to file: quarto convert doc.ipynb --output doc.qmd

Collaboration between multi-lingual teams

Edit: Replaced mispelling of “tookis” with “toolkit”

Extending Quarto with extensions

{{< fa thumbs-up >}} 

---
title: "Cool Company 2022 Presentation"
format: coolco-revealjs
---

Quarto Publish

quarto publish --help

  Usage:   quarto publish [provider] [path]
  Version: 1.0.36                          
                                           
  Description:
    Publish a document or project. Available providers include:
                                                               
     - Quarto Pub (quarto-pub)                                 
     - GitHub Pages (gh-pages)                                 
     - RStudio Connect (connect)                               
     - Netlify (netlify)                                       

What about for Data Science at Work?

• Use it in RStudio Workbench (v2022.07.1) and RStudio Connect (v2022.07.0)!

Quarto, crafted with love and care

Development of Quarto is sponsored by RStudio, PBC. The same core team works on both Quarto and R Markdown:

• Carlos Scheidegger (@cscheid)

• Charles Teague (@dragonstyle)

• Christophe Dervieux (@cderv)

• J.J. Allaire (@jjallaire)

• Yihui Xie (@yihui)

Here is the full contributors list. Quarto is open source and we welcome contributions in our github repository as well! https://github.com/quarto-dev/quarto-cli.

Quarto

• Batteries included, shared syntax across output types and languages
• Choose your own editor and your preferred data science language
• RMarkdown still maintained, but majority of new features built into Quarto

Follow @quarto_pub or me @thomas_mock on Twitter to stay up to date!

Why the name “Quarto”?¹